MODELING THE DIFFUSION OF DIGITAL BANKING ADOPTION IN UZBEKISTAN: EVIDENCE FROM TBC BANK USING THE BASS DIFFUSION MODEL AND A HYBRID REGRESSION APPROACH

This study models the diffusion dynamics of digital banking adoption in Uzbekistan using TBC Bank as acase study. Building on the Bass diffusion framework, customer acquisition is conceptualized as a combined effect ofinnovation-driven adoption and imitation-driven adoption amplified by network effects. Using historical data for 2019–2024,diffusion parameters are estimated through nonlinear curve fitting, and adoption trajectories are forecast through 2030.The baseline Bass model suggests that the number of registered customers may approach approximately 19.9 millionby 2030, with the most rapid growth expected during 2025–2027, followed by gradual deceleration. However, standalonediffusion estimates exhibit non-trivial forecasting errors when compared with observed customer data, reflecting themodel’s limited capacity to account for demographic trends and market shocks. To enhance predictive accuracy, a hybridspecification combining polynomial trend regression with Bass-type diffusion components is proposed. The hybrid modeldemonstrates substantially lower error metrics and closer alignment with observed adoption dynamics. Overall, thefindings support the applicability of diffusion modeling for strategic planning in emerging digital banking markets, whileemphasizing the necessity of integrating demographic, competitive, and regulatory factors into forecasting frameworks.